def test_to_from_bytes(image):
net = Network.load('tiny-yolo')
data = net.to_bytes()
results = net(image)
loaded = Network().from_bytes(data)
results2 = net(image)
assert results == results2
def test_evaluate(image, box_labels):
net = Network.load("tiny-yolo")
acc = net.evaluate([image], [box_labels])
assert 'fp' in acc
assert 'fn' in acc
assert 'tp' in acc
assert 'r' in acc
assert 'p' in acc
assert 'f' in acc
def test_update(image, box_labels):
net = Network.load("tiny-yolo")
for i in range(10):
loss = net.update([image], [box_labels])
print(loss)
def test_detection_data(image, box_labels):
net = Network.load("tiny-yolo")
data = DetectionData([image], [box_labels], net.width, net.height,
net.max_boxes, net.num_classes)
def test_detect(image):
net = Network.load("tiny-yolo")
result = net(image)
def test_load():
net = Network.load("tiny-yolo")
def test_init():
nn = Network()
def test_update(image, box_labels):
net = Network.load("tiny-yolo")
for i in range(10):
loss = net.update([image], [box_labels])
print(loss)
def test_detection_data(image, box_labels):
net = Network.load("tiny-yolo")
data = DetectionData([image], [box_labels],
net.width, net.height, net.max_boxes, net.num_classes)
def test_detect(image):
net = Network.load("tiny-yolo")
result = net(image)
def test_from_disk(image):
net = Network().from_disk(Path('lightnet/data/tiny-yolo').resolve())
results = net(image)
assert results is not None
def test_load():
net = Network.load("tiny-yolo")